Vehicle detection devices are widely used in vehicle operation and instrument control systems as well as information provision systems that provide useful information to a driver of a vehicle. For example, there are advanced driver assistance systems such as Adaptive Cruise Control (ACC) to ease the burden of driving on the driver. Such vehicle control systems have various features, such as automatic braking or alarms to avoid collision or relieve the shock of collision, and vehicle speed control to maintain a minimum safe inter-vehicular distance.
To improve performance, it is necessary to be able to recognize (identify) other vehicles around one's own vehicle. Therefore, various vehicle recognition devices have been proposed.
For example, unexamined Japanese patent application publication no. 2010-14706 (JP-2010-14706-A) describes a vehicle detection system that irradiates with a laser beam a predetermined area through which a vehicle passes within the imaging area of the system and produces an image showing a three-dimensional form of the vehicle that passes through the predetermined area using the reflected laser beam to improve characteristic detection accuracy used for identifying the vehicle appearing in the imaging area.
Most typical vehicle detection devices identify an image area where a vehicle traveling on the road appears using differences in luminance within the image. However, since the captured image contains many noise components (luminance information that degrades identification accuracy), it is not possible to accurately identify other vehicles simply by the luminance of the image.
JP-2009-295963-A describes a method in which two polarized images taken by an imaging device are divided into respective predetermined processing areas, calculates a degree of difference in polarization (hereinafter also simply “polarization difference”) that is the ratio of the difference in luminance between each processing area of the two polarized images to the total luminance thereof, and identifies a three-dimensional object on the road using the calculated result. In detail, based on the calculated polarization difference, adjacent processing areas corresponding to the identification object are identified as an image area of the identification object. According to this method, three-dimensional objects in an imaging area can be identified with a high degree of precision even in situation in which objects cannot be identified with a high degree of precision by a typical method using the difference in luminance because there are no clear difference in luminance. However, the detection accuracy of systems like those described above can be adversely affected by weather and road conditions that diminish or conversely exaggerate contrast, such as wet road surfaces, cloudy or very sunny weather, or alternating sun and shade.